Systems and methods for evaluating human eye tracking

ABSTRACT

Systems and methods are disclosed for evaluating human eye tracking. One method includes receiving data representing the location of and/or information tracked by an individual&#39;s eye or eyes before, during, or after the individual performs a task; identifying a temporal phase or a biomechanical phase of the task performed by the individual; identifying a visual cue in the identified temporal phase or biomechanical phase; and scoring the tracking of the individual&#39;s eye or eyes by comparing the data to the visual cue.

RELATED APPLICATION

This application claims the benefit of priority to U.S. ProvisionalPatent Application No. 61/640,781, which was filed on May 1, 2012, theentirety of which is incorporated herein by reference.

TECHNICAL FIELD

Various embodiments of the present disclosure relate generally toevaluating human eye movement. More specifically, exemplary embodimentsof the present disclosure relate to systems and methods for tracking andscoring human eye movement, and to recommending tasks to improve motorand cognitive skills based on eye movement.

BACKGROUND

Professionals or experts who have a vast amount of experience with amotor and/or cognitive task are often admired for their physicalqualities, such as strength, speed, and coordination. They are alsoadmired for qualities that are less evident, such as being in the rightplace at the right time and for the ability to strategically “out smart”a difficult situation. These more subtle qualities may be indicative ofa proficiency in cognitive understanding. Research has found thatprofessionals or experts who have a vast amount of experience in avariety of different tasks have efficient and effective cognitiveprocessing, as compared to less skilled individuals.

An indication of cognition is evidenced by where one looks in order todetect and utilize the most important information in an environment. Eyemovements reflect where a person is looking and searching in theenvironment, which may be referred to as “visual search.” Visual searchpatterns are typically not random but instead may be learned responsesto environmental stimuli. Research has found that optimal visual searchand selection patterns develop through experience and are different forexperts and novices. One example includes soccer experts, who look at akicker's hip (a pre-contact cue) to accurately determine and quicklyreact to the direction where the ball is going. Novices, comparatively,tend to focus on the ball, causing a longer time to make a decision andto initiate a movement.

Typically, experts show systematic visual search patterns from oneviewing to the next and repeatedly look at the same locations to detectinformation. Still further, research has found that experts selectivelyand consistently attend to the most salient aspects when watching thetask in which they are proficient. The visual search patterns of expertsenable them to produce significantly higher numbers of correct responsesregarding expected outcomes. As another example, expert tennis playersare often able to determine the type of spin and direction of the ballfrom understanding visual components that are present within theenvironment even before the ball is contacted. Expert tennis players areable to do this better than those with less experience. Another exampleincludes expert drivers who are able to search within their environmentand “read” the road in order to avoid potential hazards. Expert drivershave more efficient cognitive and visual search strategies, enablingthem to reduce the “cognitive load” and in turn “freeing up” valuableprocessing space should an unexpected event occur on the road, such as achild running across the road after a ball. Experts also reportsignificantly higher levels of confidence in their responses than donovices.

Decision making capabilities can be affected by visual search patterns.One example includes law enforcement officers responding to a domesticviolence situation. As the situation increases in tension, experiencedpolice officers look at the hands of the violent person, whereasinexperienced officers look at the face of the violent person, and werelate in seeing a gun being drawn, as well as significantly less likelyto make the correct decision to shoot or not-shoot. The visual searchpatterns of experts also may enable them to initiate a movement fasterthan novices, such as pressing a brake in a car, running toward alocation to intercept a ball, or firing a weapon.

The quality of motor responses also has been found to differ when lesseffective visual search patterns are used between people of similarskill level. For example, statistics have tested the quality (depth andaccuracy) of service return between college level tennis players whilemeasuring their visual search patterns on the tennis court. Resultsrevealed that the players with less salient visual search behaviors werejudged lowest in quality of service return. Hence, the cognitiveunderstanding that experts have when watching a skill is evidenced viasuperior visual search strategies that provide them with an ability toanticipate more accurately than those with less experience and lesseffective visual search. This capacity also has been shown to relate tofaster motor responses of a higher quality performance.

Effective visual search may be particularly important when watching anevent unfold rather than reacting to the consequence of an event. Forinstance, looking for the baseball from a pitcher while standing in thebatting position will provide little help in hitting the baseball,especially when the ball is traveling too fast for vision to track theball. Instead, effective visual search involves looking at biomechanicalcues within the motion of the pitch (e.g., arm rotation, grip, releasepoint) in order to effectively read the type and velocity of the pitch.

Furthermore, the eye can track an object with precision and using focalvision only when there is slow relative movement between the observerand the object. The eyes can smoothly move together following the objectuntil visual angular velocities reach 40 to 70 degrees per second. Inobserving human movement, this translates to surprisingly slowmovements, like a person walking (3 mph) slowly past an observer sixfeet away. Therefore, when a task is occurring very fast, it may notmatter if a person has perfect visual acuity and visual strength. Whatmay matter is if they have effective visual search that enables them topick up early occurrences within biomechanical phases (or pre-cues) thatpresent themselves more slowly and help predict future outcomes, such asvelocity, spin, and direction.

Thus, there is a need for systems and methods to evaluate human eyemovement. In addition, there is a need for systems and methods to trackand score individuals' eye movements, and recommend training tasks forindividuals to improve their visual search and other eye movements.

SUMMARY OF THE DISCLOSURE

According to certain embodiments, methods are disclosed for evaluatinghuman eye tracking. One method includes: receiving data representing thelocation of and/or information tracked by an individual's eye or eyesbefore, during, or after the individual performs a task; identifying atemporal phase or a biomechanical phase of the task performed by theindividual; identifying a visual cue in the identified temporal phase orbiomechanical phase; and scoring the tracking of the individual's eye oreyes by comparing the eye location data to the visual cue.

According to certain embodiments, systems are disclosed for evaluatinghuman eye tracking. One system includes a data storage device storinginstructions for evaluating human eye tracking; and a processorconfigured to execute the instructions to perform a method including:receiving data representing the location of and/or information trackedby an individual's eye or eyes before, during, or after the individualperforms a task; identifying a temporal phase or a biomechanical phaseof the task performed by the individual; identifying a visual cue in theidentified temporal phase or biomechanical phase; and scoring thetracking of the individual's eye or eyes by comparing the data to thevisual cue.

According to certain embodiments, a computer readable medium isdisclosed storing instructions that, when executed by a computer, causethe computer to perform a method of evaluating human eye tracking, themethod including receiving data representing the location of and/orinformation tracked by an individual's eye or eyes before, during, orafter the individual performs a task; identifying a temporal phase or abiomechanical phase of the task performed by the individual; identifyinga visual cue in the identified temporal phase or biomechanical phase;and scoring the tracking of the individual's eye or eyes by comparingthe data to the visual cue.

Additional objects and advantages of the disclosed embodiments will beset forth in part in the description that follows, and in part will beapparent from the description, or may be learned by practice of thedisclosed embodiments. The objects and advantages of the disclosedembodiments will be realized and attained by means of the elements andcombinations particularly pointed out in the appended claims.

It is to be understood that both the foregoing general description andthe following detailed description are exemplary and explanatory onlyand are not restrictive of the disclosed embodiments, as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of this specification, illustrate various exemplary embodiments andtogether with the description, serve to explain the principles of thedisclosed embodiments.

FIG. 1 is a conceptual illustration of an exemplary environment in whichthe disclosed systems and methods may be used to evaluate individuals'eye movements, and recommend training tasks for individuals to improvetheir visual search and other eye movements, according to an exemplaryembodiment of the present disclosure;

FIG. 2 is a block diagram of exemplary systems for evaluatingindividuals' eye movements, and recommending training tasks forindividuals to improve their visual search and other eye movements,according to an exemplary embodiment of the present disclosure;

FIG. 3 is a flow diagram of an exemplary method for evaluatingindividuals' eye movements, and recommending training tasks forindividuals to improve their visual search and other eye movements,according to an exemplary embodiment of the present disclosure;

FIG. 4 is a flow diagram of another exemplary method for evaluatingindividuals' eye movements, according to an exemplary embodiment of thepresent disclosure;

FIG. 5 is a flow diagram of another exemplary method for evaluatingindividuals' eye movements, according to an exemplary embodiment of thepresent disclosure;

FIG. 6 is a schematic diagram of a framework for evaluating and scoringindividuals' eye movements, according to an exemplary embodiment of thepresent disclosure;

FIG. 7 is a flow diagram of another exemplary method for displayingevaluations of individuals' eye movements and recommended training tasksfor individuals to improve their visual search and other eye movements,according to an exemplary embodiment of the present disclosure;

FIG. 8 is a schematic diagram of an exemplary display of evaluations ofindividuals' eye movements and recommended training tasks forindividuals to improve their visual search and other eye movements,according to an exemplary embodiment of the present disclosure;

FIG. 9 is a schematic diagram of an exemplary display of evaluations ofindividuals' eye movements and recommended training tasks forindividuals to improve their visual search and other eye movements,according to an exemplary embodiment of the present disclosure;

FIG. 10 is a schematic diagram of an exemplary display of evaluations ofindividuals' eye movements and recommended training tasks forindividuals to improve their visual search and other eye movements,according to an exemplary embodiment of the present disclosure;

FIG. 11 is a schematic diagram of an exemplary display of evaluations ofindividuals' eye movements and recommended training tasks forindividuals to improve their visual search and other eye movements,according to an exemplary embodiment of the present disclosure;

FIG. 12 is a schematic diagram of an exemplary display of evaluations ofindividuals' eye movements and recommended training tasks forindividuals to improve their visual search and other eye movements,according to an exemplary embodiment of the present disclosure; and

FIG. 13 is a schematic diagram of an exemplary display of evaluations ofindividuals' eye movements and recommended training tasks forindividuals to improve their visual search and other eye movements,according to an exemplary embodiment of the present disclosure.

DESCRIPTION OF THE EMBODIMENTS

Reference will now be made in detail to the exemplary embodiments of thedisclosure, examples of which are illustrated in the accompanyingdrawings. Wherever possible, the same reference numbers will be usedthroughout the drawings to refer to the same or like parts.

In view of the background and problems outlined above, systems andmethods are disclosed in which motor skills, cognition, and/orkinesiology of a participant may be improved through an iterativeprocess of tracking eye movement, scoring the observed eye movement,reporting or displaying the scoring to the participant, recommendingtraining to the participant based on the scores or observed eyemovement, and repeating the process after training has occurred. Certainembodiments of the presently disclosed methods may also includeselective modification or combining scores to adjust measurement andtarget values.

Participants of the present embodiments may include any people desiringto improve their motor skills, cognition, and/or kinesiology, such asany individuals who perform physical activities that require observationand decision making ahead of physical or mental action. Theseparticipants can include athletes, pilots, drivers, heavy machineoperators, lab equipment technicians, physicians, law enforcementprofessionals, and/or any other individuals involved in actions thatrequire a cognitive process in order to respond more effectively andefficiently. Alternatively, the participants may be learning orcognitively impaired individuals seeking to improve their mental andphysical abilities.

FIG. 1 is a conceptual illustration of an exemplary environment in whichthe disclosed systems and methods may be used to evaluate individuals'eye movements, and recommend training tasks for individuals to improvetheir visual search and other eye movements, according to an exemplaryembodiment of the present disclosure. Specifically, FIG. 1 depicts anathlete, i.e., a baseball player 100 engaged in a task of observationand decision making ahead of mental and physical action, i.e., hitting abaseball 102. In view of the participants listed above, it should beappreciated that, although FIG. 1 depicts a baseball player for purposesof illustration, the presently disclosed systems and methods areapplicable to any individuals engaged in actions that require acognitive process in order to respond more effectively and efficiently.

FIG. 1 depicts the athlete 100 as wearing an eye tracking device, thedevice including, for example, a plurality of cameras 104. In addition,FIG. 1 depicts a plurality of remote cameras 106, which may be pointedat the athlete 100 and configured to track and image the athlete's eyes.That is, both wearable cameras 104 and remote cameras 106 may beconfigured to follow the movement of the athlete's eyes, such as theathlete's irises and/or pupils. The wearable cameras 104 and remotecameras 106 may also be configured to generate video images of theathlete and the athlete's eyes before, during, and after the physicaldecision making activity, such as striking a target, e.g., baseball 102.Again, it should be appreciated that athlete 100 may alternatively be amachine operator, musician, physician, etc.

In one embodiment, wearable cameras 104 and/or remote cameras 106 may beprovided with additional sensors, such as a heat sensing device, a GPSdevice, a radio frequency ID (“RFID”) device, or any other sensors thataid in the detection of human eyes, the location and/or orientation ofthe human eyes, and/or the location and/or orientation of the wearablecameras 104 and/or remote cameras 106. In one embodiment, wearablecameras 104 and/or remote cameras 106 may include, but are not limitedto webcams, video cameras, remote eye trackers, mobile phones, and/ortablet computers. Wearable cameras 104, in particular, may also oralternatively include or be incorporated into spectacles, visors,helmets, implanted devices, and/or contact lenses. Wearable cameras 104and/or remote cameras 106 may also include or be provided incommunication with physiological monitors, neuroimaging devices, andbiomechanical technologies for virtual reality and simulationtechnologies use with eye data and other scoring or grading. Inaddition, the methods and systems of the disclosed embodiments may beused with other devices to track eye movements.

FIG. 2 is a block diagram of exemplary systems for evaluatingindividuals' eye movements, and recommending training tasks forindividuals to improve their visual search and other eye movements,according to an exemplary embodiment of the present disclosure.Specifically, FIG. 2 depicts an eye evaluation system 110, a pluralityof network resources 112, and a plurality of client devices 108, allprovided in communication with an electronic network 101, such as theInternet.

In one embodiment, client devices 108 may be devices owned and/or usedby one or more people or organizations affiliated with, or incommunication with, an operator of eye evaluation system 110. In oneembodiment, client devices 108 may be used by customers or clients ofthe operator of eye evaluation system 110. For example, people ororganizations desiring to have their eyes (or members' or employees'eyes) evaluated may use client devices 108 to send and receiveinformation from eye evaluation system 110. In one embodiment, clientdevices 108 may send to eye evaluation system 110 one or more of:registration information, biometric information, eye information,activity information, and so on. Client devices 108 may also receivefrom eye evaluation system 110 one or more of: eye tracking information,eye scoring information, recommended training tasks, reports, and so on.In one embodiment, client devices 108 may be computers or mobile devicesthrough which customers of an eye evaluation entity interact with eyeevaluation system 110.

In one embodiment, the devices of clients 108 may include any type ofelectronic device configured to send and receive data, such as websitesand multimedia content, over electronic network 101. For example, eachof the devices of clients 108 may include a mobile device, smartphone,personal digital assistant (“PDA”), tablet computer or any other kind oftouchscreen-enabled device, a personal computer, a laptop, and/or serverdisposed in communication with electronic network 101. Each of thedevices of clients 108 may have a web browser and/or mobile browserinstalled for receiving and displaying electronic content received fromone or more of web servers affiliated with the eye evaluation system110. Each of client devices 108 may have an operating system configuredto execute a web or mobile browser, and any type of application, such asa mobile application.

Eye evaluation system 110 may include any type or combination ofcomputing systems, such as handheld devices, personal computers,servers, clustered computing machines, and/or cloud computing systems.In one embodiment, eye evaluation system 110 may be an assembly ofhardware, including a memory, a central processing unit (“CPU”), and/oroptionally a user interface. The memory may include any type of RAM orROM embodied in a physical storage medium, such as magnetic storageincluding floppy disk, hard disk, or magnetic tape; semiconductorstorage such as solid state disk (SSD) or flash memory; optical discstorage; or magneto-optical disc storage. The CPU may include one ormore processors for processing data according to instructions stored inthe memory. The functions of the processor may be provided by a singlededicated processor or by a plurality of processors. Moreover, theprocessor may include, without limitation, digital signal processor(DSP) hardware, or any other hardware capable of executing software. Theuser interface may include any type or combination of input/outputdevices, such as a display monitor, touchpad, touchscreen, microphone,camera, keyboard, and/or mouse. Eye evaluation system 110 may beconfigured to send and receive information from network resources 112and/or clients 108 over the electronic network 101. In one embodiment,eye evaluation system 110 may be in direct local contact with one ormore of network resources 112.

In one embodiment, network resources 112 may include any type of deviceconfigured to collect and send useful information to eye evaluationsystem 110 for tracking and scoring eye movement. For example, networkresources 112 may include one or more of: wearable cameras 104 and/orremote cameras 106, one or more sensors, such as a heat sensing device,a GPS device, an RFID device, or any other sensors that aid in thedetection of human eyes, the location and/or orientation of the humaneyes, and/or the location and/or orientation of the wearable cameras 104and/or remote cameras 106. In one embodiment, network resources 112 mayinclude, but are not limited to webcams, video cameras, remote eyetrackers, mobile phones, tablet computers, spectacles, visors, helmets,implanted devices, and/or contact lenses. In one embodiment, one or moreof network resources 112 may be configured with network adapters tocommunicate information to eye evaluation system 110 over network 101.Alternatively, or additionally, one or more of network resources 112 maybe configured to transmit and receive information from eye evaluationsystem 110 directly over a local connection. Network resources 112 maybe owned and operated by an operator of one or more of: eye evaluationsystem 110, client devices 108, or even an outsourced third party, suchas an eye tracking specialist.

As will be described in more detail below, eye evaluation system 110 maybe configured to receive information, such as eye location and movementinformation, participant information, etc., either from client devices108, network resources 112, and/or any other location over the network101, and process the received information to perform various methods oftracking and scoring eye movement, and recommending training tasks toparticipants to improve eye movement, consistent with the exemplarymethods described below.

FIG. 3 is a flow diagram of an exemplary method for evaluatingindividuals' eye movements, and recommending training tasks forindividuals to improve their visual search and other eye movements,according to an exemplary embodiment of the present disclosure.Specifically, FIG. 3 depicts a method 200, which may be performed byboth an operator of eye evaluation system 110 and a participant, e.g.,an individual or entity desiring to improve eye movement.

As shown in FIG. 3, method 200 may include donning an eye tracker (step202). For example, an individual may don one of wearable cameras 104,whether implemented in a pair of glasses, a visor, a helmet, a pair ofcontacts, and so on. Alternatively or additionally, the participant maysimply position himself or herself in the view of one or more remotecameras 106. Method 200 may then include engaging in a task (step 204).For example, as discussed above, the participant may engage in any taskthat involves decision making before performing a physical action, suchas a sports activity (e.g., swinging a baseball bat, a golf club, a footat a ball, etc.), landing a plane, turning a corner, loading a pallet,performing a surgical procedure, etc.

Method 200 may then include assessing the participant's eye movement(step 206). In one embodiment, assessing the participant's eye movementmay include transmitting data collected from one or more eye trackers toan external source (step 216), storing the data (step 218), andanalyzing the participant's data (step 220). For example, data may beobtained from one or more of wearable cameras 104 and remote cameras106, and transmitted to eye evaluation system 110. In one embodiment,the participant's eye tracking data may be analyzed according to themethods described below with respect to FIGS. 4-6. Specifically, theparticipant's eye movement data may be analyzed so as to generate one ormore scores, including one or more of a “target score,” a “cognitiveload score,” and a “stress indicator score,” as will be described inmore detail with respect to FIGS. 4-6.

Method 200 may then include making comparisons between the analysis ofthe participant's eye movement and the eye movement of otherparticipants in the same or different age and skill levels (step 208).In certain embodiments, a target score, cognitive load score, and stresspotential indicator score (both ideal scores and actual scores) may bedetermined based on skill level. In addition, those scores may becompared to ideal visual search levels for a particular skill level foreach specific task determined by expert level subjects' visual searchpatterns. In some embodiments, measuring skill level and/or diagnosinglevels of proficiency may occur at various times in the present andfuture. Measuring skill levels may also include implementing predictivereasoning equations and/or scores.

In one embodiment, method 200 may then include either or both of:recommending training programs for in-task performance (step 210) andrecommending supplementary training programs (step 212). In oneembodiment, method 200 may include developing and selectingon-field/court drills or on- or off-court games based on the comparisonsin order to facilitate learning and improve performance of theparticipant or team. In one embodiment, recommended training programsfor in-task performance (step 210) may include recommending on-field oron-court training drills, whereas recommending supplementary trainingprograms (step 212) may include tasks such as practicing using a videogame system or virtual simulator.

In one embodiment, recommending in-task performance training programs instep 210 may include recommending training drills developed based onscientific guidance that provides information on the best way to learn,the process of learning, and/or how people learn to specifically improveperceptual skill training. Training drills may also be developed via intask experiences, for example, from coaches and users. This informationmay then be used to develop training drills that direct the eyes and/orthoughts to engage in certain behaviors and not others.

In one embodiment, steps 210 and/or 212 may include recommendingtraining drills that are progressive in nature based on a user's (orgroup of users') eye movement score obtained in step 206. In oneembodiment, scores may range from 0-3, 4-7, and 8-10. If a user scoresfrom 0-3, the training drill may be broader in nature with an emphasison correcting the general characteristics of the eyes and thoughts. Ascore of 4-7 may generate a training drill that is more specific, forexample, including informing the user to look at a specific location andspecific movements in time. Finally, a score of 8-10 may generate adrill that is highly specific and sensitive, for example, includinglooking within a certain degree of visual angle with specific on-set andoff-set times while having to interpret what is being seen.

In one embodiment, the process for generating scores and training drillsmay include, the participant engaging in the task (step 204),transmitting data to the eye score servers (step 216), scoring the taskusing an eye score scoring tool (step 220) to generate a specific score,e.g., based on a specific moment in time and/or a specific locationand/or eye behavior; and linking scores for each moment in time to aspecific database code that pulls, e.g., a training recommendation videointo a report for the user to access (steps 210, 212).

Method 200 may then include reassessing (step 214), such as by repeatingsteps 216-220. In one embodiment, eye evaluation system 110 may identifyand define an overall visual search strategy recommended for theparticipant and the activity being performed and intended to beimproved, e.g. reducing distractions and information intake or improveddecision making. In one embodiment, eye evaluation system 110 mayprovide generic components of effective visual search for theparticipant and defined activity, e.g. level gaze, like an airplanelanding, stable gaze, like a tripod, in some cases also consideringcognitive load of participant and related activity.

FIG. 4 is a flow diagram of another exemplary method for evaluating andscoring individuals' eye movements, according to an exemplary embodimentof the present disclosure. Specifically, FIG. 4 depicts another method300 for gathering eye movement data, analyzing eye movement data, andscoring eye movements. In certain embodiments, one or more scoresdetermined according to method 300 may be referred to as a “targetscore.”

In one embodiment, method 300 may include gathering data on where an eyeis located at various temporal aspects (step 302). For example, eyemovements may be collected from a variety of eye tracking or similar eyelocation data collection devices, such as the wearable or remote cameras104, 106 (FIG. 1) or network resources 112 (FIG. 2).

Method 300 may also include replaying video of performing a task alongwith special effects (step 304). For example, special effects mayinclude highlighting, enlarging, reducing, blocking, slowing, speedingup video for assessment and/or training purposes. Of course, method 300may use any other techniques to enhance or replay video of a task inorder to improve analysis and understanding of motion or positions ofbody parts, cues, and/or eye positions in a video.

Method 300 may also include breaking down biomechanical and temporalphases of the performed task (step 306). In one embodiment, abiomechanical phase may be an interval of bodily movement and a temporalphase may be a time interval. For example, eye evaluation system 110 mayidentify and define specific biomechanical phases of movement to beimproved by evaluating the eye movement of a participant and thesubsequent decision making carried out by the participant. Within aspecific skill, various temporal phases may be identified based onbiomechanical, social interaction, and various other important taskphases and visual search scientific research. For example, for the taskof hitting a baseball, temporal or biomechanical phases may be brokendown into a pre-wind-up phase, a wind-up phase, a pitch phase, and apost-release phase. For the task of guarding a soccer penalty kick, thetemporal or biomechanical phases may be broken down into the standbyphase, the running up phase, the windup phase, the kick phase, and thepost-kick phase. Method 300 may include breaking down phases by bothtiming, and by motions or combinations of motions by the participant orrelated individuals.

Method 300 may also include identifying visual cues at biomechanical andtemporal locations (step 308). A visual cue may be a specific visuallocation at a point in time during a task where a person may stabilizetheir vision in order to prepare for an upcoming event. For example, acue may be defined wherein a goalie should be looking at a kicker's hip,or a cue may be defined wherein a baseball player should be looking at apitcher's shoulder. Thus, in one embodiment, a cue may be a location onanother person's body, a location on a piece of equipment, a location ona vehicle, a location on a surgical instrument, a location on a playingfield, a location on a ball or sports object, and so on. In oneembodiment, eye evaluation system 110 may identify and defineappropriate cues at each biomechanical phase of the participant activitybeing monitored. For example, visual cues or ideal visual searchlocations may be determined based on scientific research, libraries ofpast data, or any other historical research. Moreover, it will beappreciated that certain cues may move with time, and so a locationwhere the participant should be looking may also move with the cue.

Method 300 may also include identifying other relevant visualinformation for performance (step 310). For example, the method mayinvolve identifying visual angles and/or visual cues. In one embodiment,visual angles may be measured by entering the size and viewing distancefrom the stimulus. Visual angle may affect a person's depth perception,which may be important for the person to exhibit temporal accuracy overdistance. For example, a parallax error may occur when the eyes do notmove together to track an object over a distance. Thus, visual cues maybe tracked over various distances and therefore may be relevant visualinformation for performance.

Method 300 may also include determining a target range for each cue(step 312). For example, target ranges may define a distance away from acue within which the individual should ideally look. In one embodiment,target ranges for ideal eye locations may be collected from a variety ofeye tracking or similar eye location data collection devices at varioustemporal phases with a static image. In some embodiments, a target rangemay be relatively static (e.g., look within 50 mm of the center of thegoalpost), whereas in other embodiments, a target range may expand ornarrow with time. In one embodiment, various ranges of temporal phasesmay be used to score a level of proficiency in the specific skill at thespecific temporal phase. For each important temporal phase, varioustarget ranges may be created to score individuals based on skill level,i.e. beginner through elite levels. For example, a target range for anexpert may be narrower than a target range for a beginner.

Method 300 may also include determining a target range for each cuepoint (step 314). Specifically, in addition to determining a targetrange for a cue generally, such as, looking within 25 mm of the centerof a baseball, a target range may be generated for each cue, at eachpoint in time within a temporal phase of interest. In other words, as abaseball travels from a pitcher to a hitter, the cue itself is movingand the range of coordinates defining the target range may also move.Thus, a target range for each cue point may define a plurality of targetranges that change over time based on the movement of a cue.

Method 300 may then involve calculating a target score based on acomparison of where a participant looked to the individual's targetrange, for one or more cues in one or more temporal phases of interest(step 316). Specifically, method 300 may generate a score for eachimportant temporal phase that coincides with the target range previouslydetermined for the specific skill level of the individual. An overallscore may then be generated by combining the score of each importanttemporal phase. In one embodiment, the target score, whether calculatedfor each temporal phase, each cue, or an overall score, may becalculated according to the embodiments of FIGS. 5 and/or FIG. 6, asdescribed below.

Method 300 may also include comparing the calculated target score to anaspired or ideal score (step 318). For example, based on the scoresand/or all results of each important temporal phase and/or the combinedscore, the individual may receive a specific report and/or images ofeach temporal phase with their specific eye locations, and comparisonsto ideal scores and/or eye locations. This report may compare andexplain the score and/or training recommendations to help achieve thesought after eye location at each important temporal phase. Anexplanation of the importance of eye location within the sought aftertarget range may also be provided in the report. Based on this report,various in-task and related-to-task training tools may be recommended tothe individual to be applied, including training games, video games,training drills and/or other training programs, as described above.

Embodiments of method 300 may therefore include conducting data analysisand/or comparisons by storing a participant's visual search patterns,plotting a visual search pattern over time, generating algorithms andreference points to provide feedback to the participant on their visualsearch patterns compared to others, and reporting on proficiencies andgaps in visual search performance. Embodiments may also includeautonomically tracking and gathering eye movements of a participant or ateam, generating a target score, and comparing the gathered data andtarget score against a benchmark. This comparison may includeidentifying where a participant looks based on his or her skill level,and identifying the emotional state of the participant and whether ornot this emotional state is compromised.

Method 300 may also include tracking ongoing assessments (step 320). Inother words, method 300 may then include gathering further data,determining new target ranges, and calculating new scores, based onlater rounds of performing the task, for example, to determine theeffectiveness of training recommended, such as in steps 210 and 212 ofFIG. 3. Reassessment and/or reevaluation may include additional datagathering for the individual to compare with baseline assessment and/orevaluation results, including the score for each important temporalphase and/or the combined score for each important temporal phase. Theseeye locations at each important temporal phase may be compared to thepreviously determined target ranges from the individual's score and/orthe score which coincides with the target range previously determinedfor the specific skill level or the individual. Based on a participant'sscores for each important temporal phase and/or the combined score, theindividual may receive an updated specific report and/or images of eachtemporal phase with their specific eye locations. This report maycompare and explain the score, and/or all results, from evaluationand/or assessment to reevaluation and/or reassessment. All information,including but not limited to eye movement data, target ranges,individual reports, recommendations, training games, video games,training drills and/or other training programs may be accessed inelectronic form including but not limited to a password protectedwebsite, mobile application, etc.

FIG. 5 is a flow diagram of another exemplary method 400 for evaluatingindividuals' eye movements based in part on the “target score”calculated as described in FIG. 4, according to another exemplaryembodiment of the present disclosure. Specifically, FIG. 5 depicts amethod including generating a target score of a participant (step 402),such as by performing one or more steps of method 300 of FIG. 4. Method400 may also include generating a cognitive load store (step 404), aswill be described in more detail below. Finally, method 400 may includecalculating a stress indicator score (step 406), based on one or both ofthe generated target score (step 402) and generated cognitive load score(step 404). One embodiment may include generating a target score,generating a cognitive load score, and then calculating a stressindicator score based on the generated target score and the generatedcognitive load score. In one embodiment, the stress indicator score maybe calculated as the sum of the generated target score and the generatedcognitive load score.

Score/Grade Test 1 Test 2 Test 3 Target ™ 1.8 6.5 9.0 Score Cognitive+32 +12 +6 Load ™ Score Stress HIGH MEDIUM LOW Potential Indicator ™Grade

Step 404: Exemplary Cognitive Load Score Generation

In one embodiment, a cognitive load score may be calculated in step 404based on the number of eye movement shifts divided bybeginning-and-ending-time-points where various target ranges ofcognitive load results may be used to score cognitive load. As describedabove with respect to calculation of the target score, eye evaluationsystem 110 may calculate the cognitive load score based on informationreceived from any of cameras 104, 106, network resources 112, or anyother external sources.

As used herein, “cognitive load” may refer to the load or “effort”related to the executive control of a participant's working memory (WM).Eye tracking can be used as a tool to represent “cognitive load” as theeyes are used to process the external environment and eye movements canbe used to explore the “load” of external and internal processing ofbrain activity. For each specific task, various beginning and endingtimes may be defined, and an ideal number of shifts in eye movements maybe identified. Shifts in eye movements may include but are not limitedto fixations, saccades, and pursuit tracking. Eye movements may becollected from a variety of eye tracking or similar eye location datacollection devices. Within a specific skill, cognitive load may bedetermined based on the number of eye movement shifts divided bybeginning-and-ending-time-points during the specific task. For eachspecific task, an ideal number of shifts in eye movements may bedetermined based on skill level. Various target ranges of cognitive loadresults may be used to score the level of cognitive load for thespecific skill. For each skill, various target ranges may be created toscore individuals based on cognitive load processing level, i.e.beginner through elite levels. In one embodiment, a cognitive load scoremay be defined by the following formula:

${{cognitive}\mspace{14mu}{load}\mspace{14mu}{score}} = {\frac{{eye}\mspace{14mu}{movement}\mspace{14mu}{characteristic}}{time} \times \frac{100}{1}}$

Data gathering for an individual baseline assessment and/or evaluationmay include collecting beginning and ending times, and the number ofshifts in eye movements for the individual. These beginning and endingtimes and the number of shifts in eye movements may be compared to thepreviously determined target ranges. The individual may receive a score,which coincides with the target range previously determined for thespecific skill level of the individual. An overall score may be used bycombining the score of each beginning and ending time. Based on thescores and/or all results of each beginning and ending time and/or thecombined score, the individual may receive a specific report and/orimages and/or video of each beginning-and-ending-time-point with theirspecific shifts in eye movements. This report may compare and explainthe score and/or training recommendations to help achieve the soughtafter reduction in eye movement shifts at eachbeginning-and-ending-time-point. An explanation of the importance of eyemovement shifting within the sought after target range may be providedin the report. Based on this report, various in-task and related-to-tasktraining tools may be recommended to the individual to be applied,including training games, video games, training drills and/or othertraining programs.

Step 406: Exemplary Stress Indicator Score Generation

As described above, in one embodiment, the stress potential indicatorscore may be a combination of one or more of the target range scores andone or more of the cognitive load scores. In one embodiment, eyeevaluation system 110 may calculate the stress indicator score based onprior calculations of target range scores and stress indicator scores,and/or based on information received from external sources. In oneembodiment, for each specific task, an ideal stress indicator score maybe determined based on skill level. Various target ranges of stressindicator results may be used to score a level of potential for thespecific skill. For each skill, various target ranges may be created toscore individuals based on stress potential indicator levels, i.e.beginner through elite levels. In one embodiment, the stress indicatorscore may be calculated as the sum of the target score and the cognitiveload score. This may therefore include determining where theindividual's stress indicator score lies within a range indicating levelof stress and ultimately a representation back to the user of the levelof stress currently assessed. This representation may or may not includea depiction of a thermometer, e.g., from 1 to 100 degrees, or some othervisual representation of the user's stress indicator score, eithercompared to others and/or to a metric indicating the maximum throughminimum levels of stress possible.

Based on the scores and/or all results of one or more of the targetrange scores, and added with one or more of the cognitive load scores,the individual may receive a specific report and/or images of one ormore of their specific target range scores and added with one or more ofthe cognitive load scores. This report may compare and explain the scoreand/or training recommendations to help achieve the sought afterreduction in stress indicator score at each one or more of the targetrange scores and added with one or more of the cognitive load scores. Anexplanation of the importance of stress potential indicator score withinthe sought after target range may be provided in the report. Based onthis report, various in-task and related-to-task training tools may berecommended to the individual to be applied, including training games,video games, training drills and/or other training programs.

FIG. 6 depicts a schematic diagram of one exemplary framework forcalculating an eye tracking score of an individual, by comparison with atarget location where an individual ideally should have looked. As shownin FIG. 6, in one embodiment, a framework for calculating a target eyescore may be based on a bull's-eye arrangement and related variablesthat may be used in calculating an exemplary eye tracking score.Specifically, FIG. 6 depicts a bull's-eye arrangement having abull's-eye defined by point X_(k), Y_(k), which may be the coordinatesfor the “key value” that represents the center of the bull's-eye,representing a cue point, or where a participant ideally should havelooked. The bull's-eye arrangement of FIG. 6 also depicts an exemplarypoint X_(p), Y_(p), which may be the coordinates for the “point ofregard” (“POR”), i.e., where the participant was actually looking.

In one embodiment, calculation of a target score consistent with thebull's-eye of FIG. 6 may include one or more of the following constants:

Br—A constant indicating the bull's-eye radius (e.g. 25 mm);

Sc—A constant indicating the scale of a segment increment, which mayspecify what portion of the bull's-eye radius (Br) is used as a segmentincrement (S), where standard scales may include ⅕, ⅖, ⅓, ¼, ½;

S—A “segment increment,” or amount that each segment ring is increasedby over the bull's-eye radius (Br), where each ring is incremented bythe same segment increment amount based on the scale (Sc), such thatS=Br*Sc;

Si—A segment index, which may be the index value of the segment ringthat relates to the target score for being within that ring; and

D—A distance between the bull's-eye center and X_(p), Y_(p) (i.e., thePOR), where:

D=√{square root over ((X _(k) −X _(p))²+(Y _(k) −Y _(p))²)}

Based on the above constants and distance formula, the distance of eachring of the circle from the bull's-eye center (X_(k), Y_(k)) may becalculated by multiplying the bull's-eye radius (Br) by the scale (Sc)to determine the scale increment (S). For example, where Br=25 mm andSc=⅕ or 0.2, then S=5 mm. The segment increment (S) may then be added tothe bull's-eye radius (Br) for each segment index (Si) to get thedistance for each ring. The table below illustrates sample calculationsgiven a bull's-eye radius of 25 mm.

mm from Segment Index Bull's-eye (Si) Center Calculation 10 25 25 9 3025 + 5 8 35 25 + (5 * 2) 7 40 25 + (5 * 3) 6 45 25 + (5 * 4) 5 50 25 +(5 * 5) 4 55 25 + (5 * 6) 3 60 25 + (5 * 7) 2 65 25 + (5 * 8) 1 70 25 +(5 * 9)

Thus, the distance for each segment ring may be represented by thefollowing formula, using the segment index (Si) as a multiplier for thesegment increment (S), as follows:

Segment Distance_(Si)=Br+((Br*Sc)*(10−Si))

Therefore, when the distance (D) where the participant was looking isexactly equal to one of the segment distances, then the segment index(Si) may be defined as the participant's “target score.” In other words,the segment distance_((si)) formula above may be solved for Si, whichprovides a formula to solve for the target score where D=SegmentDistance_((si)), such that:

D=Br+((Br*Sc)*(10−Si))

and solving for Si defines the following formula:

${Si} = {10 - \left( \frac{D - {Br}}{{Br}*{Sc}} \right)}$

Thus, when Si is defined as the “target score”—also referred to as aproprietary “RightEye Score,” such a score may be defined by thefollowing formula:

${{RightEye}\mspace{14mu}{Score}} = {10 - \left( \frac{D - {Br}}{{Br}*{Sc}} \right)}$

If it is desired to expand the formula from the X,Y coordinates of thebull's-eye key center and point of regard, then the target score or“RightEye Score” may be defined by the following formula:

${{RightEye}\mspace{14mu}{Score}} = {10 - \left( \frac{\left( \sqrt{\left( {X_{k} - X_{p}} \right)^{2} + \left( {Y_{k} - Y_{p}} \right)^{2}} \right) - {Br}}{{Br}*{Sc}} \right)}$

As a result, a target score value for any distance or X,Y coordinatesmay be calculated, resulting in values from 0 to 10. As described above,a higher target score indicates that the participant was looking closeto the cue point, where as a lower target score may indicate that theparticipant was looking relatively farther away from the cue point. Asdescribed above, in one embodiment, scores may be grouped from 0-3, 4-7,and 8-10. If a user scores from 0-3, a recommended training drill may bebroader in nature with an emphasis on correcting the generalcharacteristics of the eyes and thoughts; a score of 4-7 may generate atraining drill that is more specific, for example, including informingthe user to look at a specific location and specific movements in time;and a score of 8-10 may generate a drill that is highly specific andsensitive, such as looking within a certain degree of visual angle withspecific on-set and off-set times while having to interpret what isbeing seen.

In one embodiment, this exemplary technique for generating the targetscore may adjust the scale with a smaller or larger bull's-eye radiusbased on one or more various factors, such as the distance from thesubject to target, the participant's skill level, and so on. The tablebelow depicts exemplary target score calculations given certain point ofregard and bull's-eye coordinates, and a bull's-eye radius of 25 mm.

Bull's-eye Target Radius= 25 Score Target Trial/Rep POR POR Key KeyCalculation Score Number X Y X Y Distance 1/5 Scale Adjusted 1 200 300200 300 0.0 15.0 10 2 220 330 200 300 36.1 7.8 7 3 190 320 200 300 22.410.5 10 4 180 290 200 300 22.4 10.5 10 5 150 310 200 300 51.0 4.8 4 6260 400 200 300 116.6 −8.3 0

Additional Exemplary Evaluation Metrics (i.e., Scoring)

The above-described methods of FIGS. 3-5 describe a plurality ofdifferent scores that may be used to evaluate eye movement, includingthe target score, cognitive load score, and stress indicator score.Moreover, the present disclosure describes the bull's-eye framework ofFIG. 6 as one exemplary technique for generating a target score.However, it should be appreciated that any number or type of additionalscores may be used to evaluate eye movement. The following is a list ofadditional scores or factors that may be evaluated, calculated, and/orscored, and incorporated into one or more of the target score, cognitiveload score, and stress indicator score. Any of the following scores maybe generated by eye evaluation system 110 and displayed to a clientdevice 108 in addition to the target score, cognitive load score, and/orstress indicator score. Alternatively, any of the following scores maybe calculated and incorporated as an element or component of one or moreof the target score, cognitive load score, and stress indicator score.

Visual Relax Score: In one embodiment, a visual relax score may evaluatea visual search pattern (including fixations, saccades, pursuit trackingand any other eye movement) that is seemingly random and occurs afterthe completion of one task and before a visual anchor of the next task.The visual relax period may be a low concentration time designed to helpthe individual relax and restore brain processes between tasks. Forexample, after a closed skill like hitting a baseball or putting ingolf, the user may look at a location, such as the outfield or the hole,to reset and rethink next steps. This may be recommended with someregularity and consistency from one trial to the next. The visual relaxscore may be marked as present or absent, and a time factor may or maynot be associated with the score. In one embodiment, a formula for avisual relax score may or may not be a binary “present” or “not present”recording, and/or a reporting of looking at a specific location, with orwithout a time metric, to include one or more eye movementcharacteristics.

Anchor Cue Score: In one embodiment, an anchor cue score may evaluate afixation or tracking gaze that is presented on a specific location orobject, e.g., within 3 degrees of visual angle fora minimum of 100milliseconds occurring after the visual relax and before the visualcalibration. The anchor cue may be but need not necessarily be close invisual range to the participant (e.g., within 6 feet, depending on thetask). The anchor cue may be designed to bring the participant's mentaland visual focus back to the task at hand after a time of relaxation(i.e., the visual relax). The anchor cue score may be measured byidentification of the cue and may or may not be within a close range ofthe subject performing the task. In one embodiment, the formula foridentifying the anchor cue may or may not include a distance metric, alength of time, and/or specific eye movement characteristics. Examplesmay include a bat or diamond—like shaped objected (e.g., home plate) fora baseball hitter, a racquet for a tennis player, or the ground in frontof a subject for a soccer goal keeper.

Quiet Eye Score: In one embodiment, a quiet eye score may be a fixationor tracking gaze that may be presented on a specific location or objectin the visual motor workspace within, for example, 3 degrees of visualangle for a minimum of 100 milliseconds. For example, a quiet eye may bea fixation on the rim of a basketball hoop prior to making a free throw.The onset of the quiet eye may occur prior to the final movement in thetask; the quiet-eye offset may occur when the gaze moves off thelocation by more than, for example, 3 degrees of the visual angle for aminimum of 100 milliseconds. The quiet eye may be a perception-actionvariable, in that its onset may be dictated by the onset of a specificmovement in the task.

Visual Angle Score: In one embodiment, a visual angle score may evaluatea degree of horizontal variation from center to left and/or right (x andy coordinates) measured relative to visual object(s) and scene cameraangles. One example of a visual angle score may include the angle atwhich a batter looks at the pitcher. A visual angle score may berepresented as a left to right and/or positive to negative range ofdegrees between 0-360. In one embodiment, a visual angle score mayinclude the distance the subject is from the target, and/or the heightand width of the target. The visual angle score may be a metric thatinfluences a vantage point score, described below. In one embodiment, avisual angle score may be calculated according to the formula:

${\tan\mspace{11mu} V} = {\frac{S}{D}.}$

for visual angles smaller than 10 degrees; and

${V = {2\mspace{11mu}{\arctan\left( \frac{S}{2D} \right)}}},$

for visual angles greater than 10 degrees.

Vantage Point Score: In one embodiment, a vantage point score mayinclude the visual angle score as well as the distance and/or velocityan object may be from the subject. The vantage point score may reflect aprinciple that vision will be most accurate in observing motion at rightangles to the line of sight. In one embodiment, the vantage point scoremay provide a metric indicating the difficulty in the vantage point inorder to provide feedback that includes but is not limited to headposition, body position, and/or eye position. For example, a vantagepoint score may show a 20% reduction in optimal visual qualities,measured by the vantage point score due to, e.g., a tennis playerlooking over their shoulder in a closed stance for the backhandgroundstroke instead of positioning their body in an open stance.

Viewing Time Potential Score: In one embodiment, a viewing timepotential score may compare the subject's vantage point score against anideal vantage point score in order to determine the missing potential interms of, e.g., angles, velocity, and distance. These metrics may becalculated to determine the potential increase in viewing time of thetask. Feedback may be provided to the subject from the viewing timepotential score to indicate if vantage point and appropriate bodymovement can be used to increase viewing time in order to improveperformance. One example may include a tennis player's reduction in theviewing time potential of a ball due to a closed stance on a backhandgroundstroke. For example, a possible viewing time on a ball may be 2seconds, whereas the user's actual viewing time may be 1.5 seconds. Theviewing time potential score may or may not be represented as apercentage loss, such as a 25% loss of potential.

Visual Calibration Score: In one embodiment, a visual calibration scoremay evaluate a scan path that occurs between two objects (measured at,for example, 3 degrees of visual angle for a minimum of 100milliseconds) at a minimum of one time prior to a task beginning. Oneexample of visual calibration in baseball may include looking at theplate and then to the pitcher, which could occur once or several timesin succession without the scan path deviating to another object. Thevisual calibration score may therefore reflect a participant'scompliance with a recommended or target series of calibration tasks.

Visual Lock Score: In one embodiment, a visual lock score may evaluate afixation or tracking gaze that may be located on a specific location orobject within, for example, 3 degrees of visual angle for a minimum of100 milliseconds. The onset of the visual lock may occur either after avisual calibration or after a visual relax. The visual lock score may berated by location applicability for the task. For example, prior to afast motion, e.g. a soccer penalty kick, the subject should have avisual lock on the opponent's center mass in order to begin with themost effective location for seeing the upcoming event or task.Therefore, in this case, center mass would be the bull's-eye, and if thesubject is looking at the center mass after a visual calibration orafter a visual relax, then the subject may receive the highest score.The visual lock score may drop as the subject looks away from the centerof mass. It should be appreciated that, while the quiet eye score maymeasure a fixation in any location, the visual lock score may take intoaccount the appropriateness of the location and score this locationbased on the upcoming task.

Pursuit Tracking Score: In one embodiment, a pursuit tracking score mayevaluate a participant's ability to follow an object, such as a ball,over time and distance. The pursuit tracking score may be a percentageof time tracking an object from one defined location to another within acertain range of visual accuracy around the object. The pursuit trackingscore may be given over distance and/or time traveled and represented asa percentage score and/or frame-by-frame score.

Pursuit Tracking Skill Comparison Score: In one embodiment, a pursuittracking comparison score may evaluate a percentage of time of trackingan object from one defined location to another within a range of visualangle. The pursuit tracking score may be given over distance and/or timetraveled, and represented as a percentage score. The percentage scoremay then be compared to benchmark scores from other skill levels where afurther score may be given to the subject that represents theircomparative skill level and/or where they fall within a range of scores.

Focal Tracking Ability Score: In one embodiment, a focal trackingability score may evaluate when focal vision is no longerphysiologically able to track the object due to speed over time and/orvisual space (i.e. closer versus further away). A focal tracking abilityscore may be compared with a participant's loss of visual tracking todetermine if an increase in visual tracking time may be physicallypossible. One example may be the ability to track a baseball and thedetermination of when a ball pitched at various speeds will be unable tobe seen visually at certain distances from the batter. In oneembodiment, the focal tracking ability score may be defined by thefollowing formula:

${{focal}\mspace{14mu}{tracking}\mspace{14mu}{ability}\mspace{14mu}{score}} = \frac{{speed} + {distance}}{time}$

Visual Routine Score: In one embodiment, a visual routine score mayevaluate the consistency of visual cue location (measured, for example,at 3 degrees of visual angle for a minimum of 100 milliseconds)associated with task locations over time. Similar to a visualcalibration score, the visual routine score may be a measure via a scanpath over time between two or more objects. The visual routine score maymeasure the consistency of visual cue locations across the presentationof the same and/or similar skills. For instance, during the presentationof skill 1, the scan path may be cue A to cue B to cue A. In thepresentation of skill 2, which is skill 1 repeated, if the scan pathremains the same, i.e., cue A to cue B to cue A, then the visual routinescore would be high (a desired result assuming the cues are accurate forthe task). However, if the visual scan path changes in presentation ofskill 2 (e.g. cue A to cue D to cue A) then a lower score may beassigned due to the deviation in scan path from the presentation ofskill 1 to skill 2. The visual routine score may or may not berepresented as a percentage and/or as a measure on a scale from high tolow. Frequency of the routine may or may not be considered as a metricto determine results and/or score. One example of the visual routinescore may be a tennis player viewing a server, where the first cue is onthe non-dominant hand, the second cue is the ball, and the third cue isthe contact point.

Black Hole Score: In one embodiment, a black hole score may evaluatesaccadic suppression. Saccades may include the movement of the eye at arate of, for example, less than 100 milliseconds at 3 degrees or greatervisual angle, which do not track an object over a distance, but insteadreposition eyes quickly from one target of focal vision to the next suchthat the eyes are essentially turning off as they move via a saccade tothe next fixation. An example of a saccade may be an ice hockey goalkeeper moving his eyes from one player to the next, stopping (fixating)to look at the players, but moving the eyes quickly (with saccades) fromone player to the next. A black hole score may be assigned as apercentage of time, over a task in which the eye moves at a rate of, forexample, less than 100 milliseconds at 3 degrees or greater visual angleand is not pursuit tracking. One example may be the time the ice hockeygoal keeper uses saccades to read the offensive play of the opposingteam toward goal.

${{black}\mspace{14mu}{hole}\mspace{14mu}{score}} = {\frac{{saccadic}\mspace{14mu}{eye}\mspace{14mu}{movement}\mspace{14mu}{time}}{{overall}\mspace{14mu}{task}\mspace{14mu}{time}} \times \frac{100}{1}}$

Response Time Score: In one embodiment, a response time score mayevaluate an interval of time involving both reaction time and movementtime, i.e., the time from the onset of a stimulus (e.g. gunshot) to thecompletion of the movement e.g. crossing the start or finish line.Responses may be but are not limited to motoric and/or verbal responsesand/or eye movement. Response time may be defined as follows:

response time score=reaction time+movement time

Reaction Time Scores: In one embodiment, a reaction time score mayevaluate the interval of time between the onset of a signal (stimulusand/or visual cue) and the initiation of a response (verbal and/ormotor). One example may be a sprinter in track when they hear the gunand then begin to move to respond to the “go” signal. Responses may bebut are not limited to motoric and/or verbal responses and/or eyemovement. In one embodiment, reaction time may be calculated from a “GoSignal” zero time to initiation of a response, including premotor andmotor components, to any number of stimuli/situations.

Simple Reaction Time Score: In one embodiment, a simple reaction timescore may evaluate when a situation requires only one signal and oneaction (motor, verbal or eye movement) in response. The example of thesprinter reacting to a gun (the go signal) and responding by running(the action) is an example of simple reaction time. This is the simplestform of reaction time. In one embodiment, reaction time may becalculated from a “Go Signal” zero time to initiation of response,including premotor and motor components, to one stimuli/situation.

Discriminate Reaction Time Score: In one embodiment, a discriminatereaction time score may evaluate where there is more than one signal,but only one response. For example, three objects appear on a screen: atriangle, square and circle. The athlete needs to only respond to thecircle and ignore the square and triangle. Reaction times are usuallylonger in discriminate reaction time situations than simple reactiontime, due to an increase in information processing and decision makingneeded to respond accurately to the situation. The formula fordiscriminate reaction time may or may not include an error score. In oneembodiment, reaction time may be calculated from “Go Signal” zero timeto initiation of response, including premotor and motor components, toone stimuli/situation while ignoring others.

Choice Reaction Time Score: In one embodiment, a choice reaction timescore may evaluate where there is more than one signal to which theperson must respond and each signal has a specified response. This ismay be referred to as the “If this . . . then that” reaction time. Forinstance, a training drill related to the choice reaction time score mayinclude displaying a circle on a screen, that a participant must lookat, until it disappears. If a square appears on the screen, then theparticipant must avoid looking at it. If a triangle appears on thescreen then the participant must follow it with your eyes as it movesleft and right, and so on. In one embodiment, a formula for choicereaction time may or may not include an error score. In one embodiment,choice reaction time may be calculated from a “Go Signal” zero time toinitiation of a response, including premotor and motor components, toone stimuli/situation with the correct “choice”/response.

Pre-Motor Component Score: In one embodiment, a pre-motor componentscore may evaluation time from the initiation of the “Go Signal” to thebeginning of a motor component response. This may be measured througheither biofeedback and/or psycho-physiological feedback. In oneembodiment, a pre-motor component reaction time may be calculated as areaction time—motor component.

Motor Time Component Score: In one embodiment, a motor time componentscore may evaluate time from the initiation of a motor component,measured via either biofeedback and/or psycho-physiological feedback,until the initiation of a response. In one embodiment, a motor componentreaction time may be calculated as reaction time minus a pre-motorcomponent time.

Movement Time Score: In one embodiment, a movement time score mayevaluate the interval of time between the initiation of the movement andthe completion of the movement, such as, when a sprinter begins to movein response to the gun until when she crosses the start/finish line.Another example may be when the eyes begin to move until they reachtheir target. In one embodiment, movement time may be calculated basedon the time between initiation of the response until termination of theresponse.

Inhibition Score: In one embodiment, an inhibition score may evaluatethe ability of a participant to not respond to a target, for instance,to not be distracted by the wind blowing flags beside the tennis courtor a car moving behind a sports field. The inhibition score may or maynot be measured via number of hits/looks.

Target Over/Undershoot Score: In one embodiment, a targetover/undershoot score may evaluate the amount of constant error beyondthe target, the signed deviation (+/−) from the target. For example, thescore may represent the amount and direction of error and serve as ameasure of performance bias. The over/undershoot score may be signed(+/−) and receive a distance metric. For example, 3 centimeters mayrefer to stopping 3 centimeters short of the desired target. In oneembodiment, the target over/undershoot score may be calculated based ona distance from the center of the target to center of the eye movementstopping point, adding a minus for stopping too early and a plus forovershooting

Target Miss Score: In one embodiment, a target miss score may refer tothe unsigned deviation (miss) from the target, representing the amountof error. The target miss score may include the absolute error, ameasure of the magnitude of an error without regard to direction of thedeviation. The target miss score, for example, may be 3 centimeters andrefer to the distance the eye stopped from the target, but not thedirection of the error (i.e., stopping short or overshooting). In oneembodiment, the target miss score may be calculated based on a distancefrom the center of the target to the center of the eye movement stoppingpoint.

Target Consistency Score: In one embodiment, a target consistency scoremay refer to the variable error representing the variability (orconversely, the consistency) of performance. For example, in oneembodiment, standard deviation of the users' target over/undershoot (x)may be calculated based on the score (constant error) for the series oftrials, i.e., number (n) of attempts, as follows:

$s = \sqrt{\frac{\sum\;\left( {x - \overset{\_}{x}} \right)^{2}}{n - 1}}$

Target Movement Score: In one embodiment, a target movement score mayevaluate an error involved in continuous skills, such as following aball (or object), to indicate the amount of error between theperformance curve and the criterion performance curve for a specificamount of time during which the performance is sampled. In oneembodiment, the target movement score may record whether the eye iswithin or outside of the range of a target as it moves, as opposed todistinguishing the type of eye movement characteristic. An individual'suser score may then be graphed and compared to the amount of errorbetween the performance curve and the criterion performance curve forthe length of time of the task.

${{target}\mspace{14mu}{movement}\mspace{14mu}{score}} = \frac{{time}\mspace{14mu}{on}\mspace{14mu}{target}}{{total}\mspace{14mu}{time}}$

Smooth Pursuit Eye Movement Score: In one embodiment, a smooth pursuiteye movement score may evaluate an error measure used for continuousskills, such as following a ball (or object) to indicate the amount oferror between the performance curve and the criterion performance curvefor a specific amount of time during which the performance is sampled.The smooth pursuit eye movement score may distinguish between the typeof eye movement characteristic and only include smooth pursuit eyemovements (i.e., excluding fixations or saccades). The smooth pursuitscore may be calculated as follows:

${{smooth}\mspace{14mu}{pursuit}\mspace{14mu}{score}} = \frac{{time}\mspace{14mu}{on}\mspace{14mu}{target}\mspace{14mu}{with}\mspace{14mu}{smooth}\mspace{14mu}{pursuit}\mspace{14mu}{movement}}{{total}\mspace{14mu}{time}}$

The individual user's score may be graphed and compared to the amount oferror between the performance curve and the criterion performance curvefor the length of time of the task.

Decision Making Score: In one embodiment, a decision making score mayevaluate the participant's ability to make the correct decisionregarding the outcome of the task. The decision making score may or maynot be a combination of the response time score and accuracy of responseassociated with the outcome of the task. One example may be, to look tothe right or left, high or low, to follow or not to follow a target(i.e. go or no-go) decision making. Metrics for the decision makingscore may or may not be binary (for example, 10 correct, 5 incorrect)and/or binary with response time (for example, 10 correct within 5seconds).

Direction Score: In one embodiment, a direction score may evaluate theability of the participant to follow directions of the task. During apre-task explanation and test, the score may evaluate whether the userfollowed the directions required to begin the task, such as whether auser looked at an object when asked to do so. The metrics for thedirection score may or may not be binary “Yes” or “No”, “Green light” or“Red Light,” and they may or may not be a percentage of “readiness”.

Recognition Score: In one embodiment, a recognition score may be a scorethat indicates decision accuracy that includes but is not limited toverbal and/or motoric response, with reasoning, regarding where asubject should be looking and may or may not include temporal aspects ofthe task. In certain embodiments, the task may be static or dynamic, andthe time may or may not be included in the metric. For example, the usermay be required to verbally respond to the particular play (e.g. runningplay) in American football and then must explain why he recognizes theplay as a running play. The recognition score may measure whether theathlete's response to the recognition of the play is accurate orinaccurate and the recognition score may or may not include a time torespond.

Cue Identification Score: In one embodiment, a cue recognition score mayindicate a decision accuracy that includes but is not limited to verbaland/or motoric response, without reasoning, regarding where a subjectshould be looking and may or may not include temporal aspects of thetask. In one embodiment, a task may be static or dynamic, and time mayor may not be included in the metric. For example, the user may berequired to verbally respond to the particular play (e.g. running play)in American football. Unlike the recognition score, the user does notneed to explain their reasoning for the decision to call what they sawas a “running play”. The cue identification score may measure whetherthe user's response to the cue/display is accurate or inaccurate, andmay or may not include a time to respond.

Reasoning Score: In one embodiment, a reasoning score may evaluate ameasure of a participant's quality to explain why he or she responded ina certain way to a task and/or a part of a task. A reasoning score mayinclude looking at a location, and responding with a verbal and/or motorresponse. The reasoning score may provide information on what is beingextrapolated and/or interpreted from the environment. One example may bea subject having to pick a “best response” from a list of responsesand/or explanations. The reasoning score may be a qualitative measure ora quantitative measure.

Static Visual Acuity Score: In one embodiment, a static visual acuityscore may evaluate a participant's ability to observe stationary detailin varying contrast conditions. The static visual acuity score may bedetermined by a combination of accuracy in recognition and may or maynot include time, angular velocities, and/or various contrastconditions. The static visual acuity score may represent an ability tofind relevant information within a “busy” environment. The static visualacuity score can be used to determine an athlete's ability to detectessential information, accurately and efficiently within theirenvironment. For instance, a quarterback in American football may needto determine within an instant, where his teammates are located and beable to follow them (visually) from one location to another. In oneembodiment, a formula for the static visual acuity score may be:

${{static}\mspace{14mu}{visual}\mspace{14mu}{accuity}\mspace{14mu}{score}} = {\frac{{cue}\mspace{14mu}{identification}}{{time}\mspace{14mu}{to}\mspace{14mu}{complete}\mspace{14mu}{task}}{or}\frac{\#\mspace{14mu}{of}\mspace{14mu}{cues}\mspace{14mu}{identified}}{{time}\mspace{14mu}{to}\mspace{14mu}{complete}\mspace{14mu}{task}}}$

Dynamic Visual Acuity Score: In one embodiment, a dynamic visual acuityscore may evaluate the participant's ability to observe detail whilemovement is occurring in varying contrast conditions. The dynamic visualacuity score may be determined by a combination of accuracy inrecognition, and may or may not include time, angular velocities, and/orvarious contrast conditions. The dynamic visual acuity score mayrepresent an ability to find relevant information within a “busy”environment, where objects are moving at varying speeds from variousdistances, and shapes and colors. The dynamic visual acuity score can beused to determine an athlete's ability to detect essential informationaccurately and efficiently within a changing environment. For instance,a quarterback in American football may need to determine within aninstant, where his teammates are located. In one embodiment, a formulafor the dynamic visual acuity score may be:

${{dynamic}\mspace{14mu}{visual}\mspace{14mu}{accuity}\mspace{14mu}{score}} = {\frac{{cue}\mspace{14mu}{identification}}{{time}\mspace{14mu}{to}\mspace{14mu}{complete}\mspace{14mu}{task}}{or}\frac{\#\mspace{14mu}{of}\mspace{14mu}{cues}\mspace{14mu}{identified}}{{time}\mspace{14mu}{to}\mspace{11mu}{complete}\mspace{14mu}{task}}}$

Verbalization Score: In one embodiment, a verbalization score mayevaluate a qualitative or quantitative measure of the participant'sverbal “self-talk” while engaging in a task. The metrics for this may ormay not include length of utterance/time and/or the number of positivestatements, the number of negative statements, and/or the number ofcorrective statements.

Breathing Score: In one embodiment, a breathing score may be a measureof the participant's breath rate over time, breath holds, intake andouttake time, and/or temporal phasing of breath. The breath score mayprovide an indicator of stress and exertion during an activity. This mayor may not be used in a correlational or causal fashion to furtherunderstand eye movement behaviors. In one embodiment, a breathing scoremay be calculated based on a rate of breath divided by an amount oftime.

Visual Stability Score: In one embodiment, a visual stability score maybe the length of time a fixation or gaze location remains stable(within, for example, 3 degrees of visual angle for a minimum of 100milliseconds) on a target in accordance with head tilt measured by thevisual angle score. In one embodiment, a visual stability score may becalculated based on a fixation length divided by an amount of time.

Brain Plasticity Score: In one embodiment, a brain plasticity score mayevaluate the participant's capacity to change the structure andultimately the function of the brain. Initial research indicates thatduring training exercises, gathering eye movements can be a usefulindicator of brain plasticity. The brain plasticity score may bemeasured from one testing session to the next and may or may not bemeasured at increments between testing sessions. The brain plasticityscore may be used to indicate a rate of change and adaptation based onin-task and related-to-task training tools recommended to the individualto be applied, including training games, video games, training drillsand/or other training programs. The brain plasticity score may bemeasured via the change over time in the reasoning score and/or therecognition score and/or the target score.

Predicting Potential Score: In one embodiment, a predicting potentialscore may be used to predict an individual's future level of competencyin visual search. In one embodiment, a predicting potential score may begenerated based on one or more of the above-described brain plasticityscore, dynamic visual acuity score, decision making score, reaction timescore, visual routine score, target score, cognitive load score, and/orstress potential indicator score. In one embodiment, the predictingpotential score may represent potential “upside” or “downside” rates ofthe user. For example, an individual's potential for elite performancemay be predicted using perceptual skills, including eye movementbehavior, such that elite performers can be differentiated from lesselite counterparts, even at a very early age. These scores and theirrelated data metrics may be weighted based on the task and researchresults that help define their level of importance as a predictor offuture performance.

In one embodiment, a predicting potential score may be calculated bydefining the perceptual performance parameters of importance for theparticular task, given that different tasks rely more heavily on certainparameters than others. For example, since reaction time may beimportant for baseball, the reaction time score may be included in thepredicting potential score for baseball. Whereas, if reaction time isfound to be less important for, e.g., golf, then reaction time may beomitted as a predicting potential indicator for that task.

Next, a predicting potential score may be calculated by determining aweight for each category of performance parameters deemed important forthe task. For example, in baseball, it may be determined that thereaction time score and the decision making score are equally importantindicators of predicting potential, and a third variable, e.g. the cuevariable score, may be determined to be about half as important as thereaction time score in predicting potential. As a result, the cuevariable score may be rated lower and in turn given a lower percentagein terms of the overall score. Thus, a predicting potential score forbaseball might include, for example, a reaction time score weighted at40 percent, a decision making score weighted at 40 percent, and a cueidentification score weighted at 20 percent.

Next, an individual score may be calculated for each metric ofimportance for predicting potential for this task. For example, thereaction time score may be found to be 90%, the decision making scoremay be found to be 95%, and the cue identification score may be found tobe 98%. Each component score may then be multiplied by the weightassigned above to that component. For example, if a user received a 90percent as a reaction time score, which may have been weighted as 40percent of the total grade, the method may include multiplying 0.90 by0.40 to obtain 0.36, or 36 percent. This may be repeated for any otherscores determined as being correlated to strong future performance in aparticular task. Finally, a total weighted percentage may be calculatedby adding the percentages for each category derived from the weighting.Thus, if the user received a 36 percent weighted reaction time score, a38 percent weighted decision making score, and a 19.6 percent weightedcue identification score, then 36, 38, and 19.6 may be summed to obtaina weighted average of 93.6 percent.

In one embodiment, analysis of a predicting potential score may includedetermining where a user falls compared to a standardized group of peernorms. For example, a little league baseball player with a decisionmaking score of 95% compared to a group of his peers may fall in the top1% of all his peers. This process may continue until all relevantmetrics for the task were scored and compared to metrics within the peergroup norms. One exemplary result is reflected in the table below:

Ranking Ranking Percentage Percentage (compared to Weight (Level(compared to peer group of importance peer group norms to Average forthe task of Weighted norms per determine Metric Score baseball)Percentage score) overall score) Reaction 90% 40%   36% Top 1% .004 .4Time Score Decision 95% 40%   38% Top 3% .012 1.2 Making Score Cue 98%20% 19.6% Top ½% .001 .1 Identification Score 93.6% TOTAL = 1.7 TOTAL

In one embodiment, the predicting potential score may be calculated bymultiplying the weighted percentage with the ranked percentage todetermine the overall ranking percentage, as illustrated in the tableabove. In this case, the ranking percentage may be 1.7%, meaning thatthis user is in the top 1.7% of all people in his peer group for thepredicting potential metrics for baseball. Thus, the overall rankingpercentage of this individual may suggest that he or she is a “highlyqualified” candidate, likely to become an elite baseball player in termsof the perceptual-motor skills important for performing the task.

Blink Score: In one embodiment, a blink score may refer to the timingand/or length of a blink before and/or during and/or after a task. Theblink score may provide information about “lost” vision including whenthat vision was lost within the task which may help to indicate a lossof ball tracking at a critical point in time. In one embodiment, aformula for the blink score may include a time length of blinks dividedby a length of a task.

Blind Vision Score: In one embodiment, a blind vision score may begenerated when the eye is tracking an object which may or may not changedistances and/or speeds. For example, blind vision may occur when theeye can no longer physiologically track the object due to either thedistance and/or speed of the object. The score may be presented as apercentage, a raw score, a time score, and/or an “off”/“on” score. Inone embodiment, a possible formula for the blind vision score mayinclude a time that an eye is “on,” i.e., tracking, divided by a totaltask time.

Visual Inhibition Score: In one embodiment, a visual inhibition scoremay evaluate the ability of the participant to not move the eye towardan object. This score may be reported as a binary “yes/no” score and/ora score based on overall number of inhibitions during a specific task.The visual inhibition score may be important as an indicator ofdistractibility and impulse control.

Task Parameter Information: In one embodiment, task parameterinformation may include various aspects of the task at hand, includingdistance, speed, velocity, angles, heights etc. Task parameterinformation may be relevant scientific information, including but notlimited to physics, biomechanics, perceptual-motor, mathematical,neuro-scientific, physical, etc. on what is required in order to affecta performance.

As discussed above, eye evaluation system 110 may calculate any numberor combination of the above scores based on information collected fromwearable cameras 104, remote cameras 106, and/or network resources 112.Eye evaluation system 110 may calculate any number or combination of theabove scores based on the exemplary formulas described above, andincorporate any of the above scores in calculating one or more of thetarget score, the cognitive load score, and/or the stress indicatorscore. Numerous other scores may be generated over time based on taskadditions, eye movement characteristics, eye movement behaviors and/oradditional tools added to eye movements, including, for example,psycho-physiological monitoring, biofeedback and/or biomechanical tools,and/or biometrics, such as EEG and heart rate.

Any of the above described scores may be measured based on any number ofperformance and/or learning metrics. For example, notwithstanding theexemplary formulas described above, any of the formulas may be adjustedand the scores therefore calculated, based on any of the followingphysical measurements, including: velocity data (rate of change of anobject's position over time), acceleration (change in velocity during amovement, derived by dividing change in velocity by change in time),displacement (change in spatial position during the course of amovement), kinematics (motion without regard to the force or mass),linear and angular motion, force, mass, degrees of change, degrees ofvisual angle, distance, number of trials, length of trials, time (timeof a task, reaction time, response time, movement time, etc.)

In addition, any of the scores may be calculated based oncharacteristics of the participant(s), including parameters such as:coordination, practice, competition, fatigue, motivation, retention,vigilance, monocular or binocular, central (focal) or peripheral vision,psychological refractory period, stage of learning (e.g. cognitivestage, associative stage, autonomous stage, etc.), diversification(e.g., the learner's ability to acquire the capability to modify themovement pattern according to environmental characteristics), transferof learning (positive or negative), and training (e.g., length, time,frequency, quality).

In addition, formulas and scores may be adjusted based on statisticalmetrics: qualitative statistics, quantitative statistics, error scores(e.g., constant error, absolute error, variable error, root mean squarederror), arithmetic (e.g., summing, subtracting, dividing, multiplying),standard deviations, raw score/data, statistical significance,statistical power, and so on. Further statistical testing may includebut not be limited to T-Tests, analysis of variance (ANOVA), repeatedanalysis of variance, Wilcoxon-Mann-Whitney test, chi-square test,regression, Freidman test, correlational analysis, discriminateanalysis, multivariate analysis of variance (MANOVA), and/or Cronbachalpha. In addition, formulas and scores may be adjusted based on eyemovement metrics, such as biofeedback measures, psycho-physiologicialmeasures, biomechanical measures, environmental and/or biometricmeasures, among others.

As described above, any of the scores or other information generated byeye evaluation system 110 may be presented electronically, such as bytransmission to client devices 108. For example, in one embodiment, eyeevaluation system 110 may report data to clients or customers of theentity operating eye evaluation system 110 in the form of one or morereports. Data reporting may include, but not be limited to one or moreof the following: single user reports, group reports (more than oneuser), reports across multiple groups, a single report alongside a groupreport, a report of skill level for individual users and/or groups, areport of any number of demographic variables to include but not limitedto age and/or gender reports, environmental condition reports,longitudinal reports of individuals and/or groups over more than onedata input session, a report of any eye movement characteristics and/orbehaviors for a user and/or group, a report of any psycho-physiologicaland/or biofeedback and/or biomechanical and/or biometric tool and/orenvironmental conditions with or without eye movement data, aquantitative and/or qualitative report, a report with or without videofootage, images, scores, training recommendations, temporal phases,and/or graphical representations (e.g., bar charts, line graphs, piecharts).

In one embodiment, a report may include, but be not limited to:comparison of data, displaying data, interacting with data, collatingdata, raw data displays, quantifying data beyond raw output (e.g.,summing, averaging, percentiles, angles, etc.), further data analysis(e.g., variance, effect sizes, t-tests, co-efficient, degrees offreedom, video, images, scores, displaying graphics, etc.).

FIG. 7 is a flow diagram of another exemplary method for displayingevaluations of individuals' eye movements and recommended training tasksfor individuals to improve their visual search and other eye movements,according to an exemplary embodiment of the present disclosure.Specifically, FIG. 7 depicts a method 500 for displaying one or more ofthe above calculated scores to participants and/or participants'employers, such as to client devices 108. As shown in FIG. 7, method 500may include generating an online “locker room” (step 502). Of course, a“locker room” may be any type of online user account, and may includeany alternative naming convention based on the type of participant thatthe operator of eye evaluation system 110 is catering to. Generating theonline account may include establishing web servers in communicationwith eye evaluation system 110, granting access to databases of scoresand information, and establishing user interfaces for receiving,viewing, and interacting with stored scores and data. Method 500 mayalso include applying security settings (step 504). For example, accessto the online account (or “locker room”) may be controlled at theindividual (participant) level, team level, by coaches and/or parents,agents, scouts, therapists, employers, etc.

In one embodiment, method 500 may include displaying at a client device108 the one or more calculated scores, such as the generated targetscore, cognitive load score, and/or stress indicator score (one or moreof which may be referred to as a proprietary “RightEye Score”) (step506). For example, eye evaluation system 110 may display one or morescores along with a video playback of the evaluated action or task,comparisons to other individuals, written and/or video summaries ofanalysis, recommended training drills, video or game training drills,etc., of any of the other generated information discussed above withrespect to the methods of FIGS. 3-6. Method 500 may also includedisplaying tracking progress (step 508), which may include comparingongoing assessments with previous assessments and baselines, comparingand tracking use of training tools and progress, and displaying liveperformance results (e.g., individual statistic). For example, method500 may include displaying the results of performing comparisons (as instep 208, FIG. 3), recommending training (as in steps 210, 212, FIG. 3),and reassessing/testing (as in step 214, FIG. 3). Method 500 may alsoinclude displaying ancillary information (step 510), such as performanceprogress leading to income increase, better recruiting, better drafting,meeting organizational standards, etc. Thus, method 500 may display anyof the results from performing the methods of FIG. 3-6, and relatedinformation about how those methods improve the visual search andperformance of its participants.

FIG. 8 is a schematic diagram of an exemplary display of evaluations ofindividuals' eye movements and recommended training tasks forindividuals to improve their visual search and other eye movements,according to an exemplary embodiment of the present disclosure. In oneembodiment, FIG. 8 is a screenshot of a web-based interface 800 forinteracting with eye evaluation system 110. Web-based interface 800 maybe managed or operated by eye evaluation system 110, hosted on one ormore web servers over the Internet, and displayed on one or more clientdevices 108.

In one embodiment, web-based interface 800 displays various eyeevaluation information, such as various scores and informationcalculated according to the methods of FIGS. 3-6. For example, web-basedinterface 800 may display a proprietary RightEye Score 802, which may beor include one or more of the target score, cognitive load score, and/orstress indicator score generated according to the methods describedabove. Web-based interface 800 may also display statistics associatedwith an evaluated task 804, such as how a participant's performance mayvary over time, and how a proprietary eye evaluation score may correlatewith other scores or statistics typical of the evaluated task. In thiscase, web-based interface 800 depicts a calculated eye evaluation scorein relation to a batting average calculated on different days. Althoughweb-based interface 800 depicts the display of eye evaluationinformation in relation to baseball statistics, it should be appreciatedthat the web-based interface 800 may display eye evaluation informationin relation to any other information or statistics typical of any othersport, activity, or profession, depending on the task and/or theparticipant. As shown in FIG. 8, the web-based interface 800 may alsodepict an eye evaluation score in a graph 806, along with one or moretask-specific metrics or statistics, in this case batting average, overtime. The web-based interface 800 may also display one or more trainingrecommendations 808, such as any of the training recommendationsgenerated in steps 210, 212 (FIG. 3). For example, web-based interface800 may display training videos, embed training games, or displaydescriptions of how to improve visual search and/or techniques forimproving any of the eye evaluation scores described above.

FIG. 9 is a schematic diagram of the exemplary display of evaluations ofindividuals' eye movements and recommended training tasks of FIG. 8, butalso including a display of history 810 of a participant's eyeevaluation scores and task-specific scores or metrics.

FIG. 10 is a schematic diagram of an exemplary display of evaluations ofindividuals' eye movements and recommended training tasks forindividuals to improve their visual search and other eye movements,according to an exemplary embodiment of the present disclosure. As shownin FIG. 10, the web-based interface 800 of FIG. 8 may include anassessment page 818, including a breakdown of temporal or biometricphases, related pictures, related eye evaluation scores, and recommenddrills. The assessment page 818 may also include links for participantsto view and modify account information, profile information, eyeevaluation scores, training, assessments, trades, and support. Inaddition, the assessment page 818 may include a trending scores window820. Trending scores window 820 may graph one or more eye evaluationscores in relation to a task-specific score or metric over time, in thiscase graphing batting average against an eye evaluation score over time.

FIG. 11 is a schematic diagram of another exemplary embodiment of theassessment page 818 of FIG. 10. As shown in FIG. 11, the assessment pagemay depict a plurality of static phases 826, including preparation, backswing, down swing, contact, and finish. The assessment page may alsodepict one or more related images 828, which may be images of theparticipant involved in the respective static phase, or of aprofessional or expert in an ideal stage of movement. The assessmentpage may also depict an eye evaluation score 830 associated with eachstatic phase. Finally, the assessment page may depict a trainingrecommendation 832 in relation to each static phase. As discussed above,a training recommendation may be automatically selected based on alibrary of possible training recommendations corresponding to differentscores. For example, a training recommendation may be made based onwhether it statistically improved the eye movement of others withsimilar eye evaluations or score.

FIG. 12 is a schematic diagram of an exemplary display of evaluations ofindividuals' eye movements and recommended training tasks forindividuals to improve their visual search and other eye movements,according to an exemplary embodiment of the present disclosure.Specifically, FIG. 12 shows that web-based interface 800 may include ascoring tool 850, which may include a video 852 embedded therein of aparticipant engaged in an evaluated task. In one embodiment, the scoringtool 850 may include keyframe data 854 enabling a user to evaluate thevideo 852 and define certain temporal phases (e.g., phase 1, phase 2,etc. as shown), for purposes of defining video segments and enclosed eyemovement for scoring according to the methods of FIGS. 3-6.

FIG. 13 is a schematic diagram of another exemplary display ofevaluations of individuals' eye movements and recommended training tasksfor individuals to improve their visual search and other eye movements.Specifically, FIG. 13 depicts a team window 860 of web-based interface800. As shown in FIG. 8, team window 860 may display one or more groupstats 862 associated with a team, such as statistics relating to one ormore eye evaluation scores averaged across the team. Team window 860 mayalso display a team graph 864, which may graph one or more of the abovedescribed scores as averaged across a team over time or across teammembers. Team window 860 may also depict information 866 on specificteam members relative to the whole team, such as “most improved,” “mostactive,” or “most recommended drill.” Team window 860 may also displayan average eye evaluation score 868 for an entire team. Of course, theaverage eye evaluation score may be of the target score, cognitive loadscore, and/or stress indicator score, or any other ancillary scoredescribed above, as averaged across one or more members of a team.

Other embodiments of the disclosure will be apparent to those skilled inthe art from consideration of the specification and practice of theinvention disclosed herein. It is intended that the specification andexamples be considered as exemplary only, with a true scope and spiritof the invention being indicated by the following claims.

1. A method for evaluating human eye tracking, the method including: receiving data representing the location of and/or information tracked by an individual's eye or eyes before, during, or after the individual performs a task; identifying a temporal phase or a biomechanical phase of the task performed by the individual; identifying a visual cue in the identified temporal phase or biomechanical phase; and scoring the tracking of the individual's eye or eyes by comparing the data to the visual cue.
 2. The method of claim 1, wherein the data is one or more of: image data of the individual's eye or eyes, coordinate data of the location of the individual's eye or eyes, and coordinate data of a location on which the individual's eye or eyes were focused.
 3. The method of claim 1, wherein the data is received, either locally or over a network, from a wearable eye tracker configured to obtain the data by imaging the individual's eye or eyes.
 4. The method of claim 1, further comprising: determining a target range associated with the visual cue, the target range defining an ideal viewing area around the visual cue; and scoring the tracking of the individual's eye or eyes by comparing the tracking to the determined target range.
 5. The method of claim 1, further comprising: identifying movement of the identified visual cue, the identified movement including a set of coordinates of the visual cue at each of a plurality of points in time; and determining a target range associated with each of the sets of coordinates of the visual cue.
 6. The method of claim 1, further comprising: recommending one or more training drills to the individual based on a score generated from scoring the tracking of the individual's eye or eyes.
 7. The method of claim 1, wherein scoring the tracking of the individual's eye or eyes includes one or more of: generating a target score, generating a cognitive load score, and calculating a stress indicator score.
 8. The method of claim 7, wherein the target score is generated based on a bull's-eye arrangement centered around the visual cue.
 9. The method of claim 7, wherein the cognitive load score is generated based on a number of eye shift movements detected within an interval of time.
 10. The method of claim 7, wherein the stress indicator score is calculated as the sum of the target score and the cognitive load score.
 11. The method of claim 1, further comprising calculating a predicting potential score that is predictive of the individual's potential performance in the task, as a function of one or more performance parameters identified as predictive of future performance in the task.
 12. The method of claim 11, further comprising: calculating a score for each of the one or more performance parameters predictive of potential performance in the task; determining a weight for each of the one or more performance parameters; and calculating a total predicting potential score based on the determined weights and the calculated scores.
 13. A system for evaluating human eye tracking, the system including: a data storage device storing instructions for evaluating human eye tracking; a processor configured to execute the instructions to perform a method including: receiving data representing the location of and/or information tracked by an individual's eye or eyes before, during, or after the individual performs a task; identifying a temporal phase or a biomechanical phase of the task performed by the individual; identifying a visual cue in the identified temporal phase or biomechanical phase; and scoring the tracking of the individual's eye by comparing the data to the visual cue.
 14. The system of claim 13, wherein the data is one or more of: image data of the individual's eye or eyes, coordinate data of the location of the individual's eye or eyes, and coordinate data of a location on which the individual's eye or eyes were focused.
 15. The system of claim 13, wherein the data is received, either locally or over a network, from a wearable eye tracker configured to obtain the data by imaging the individual's eye or eyes.
 16. The system of claim 13, wherein the processor is further configured for: determining a target range associated with the visual cue, the target range defining an ideal viewing area around the visual cue; and scoring the tracking of the individual's eye or eyes by comparing the tracking to the determined target range.
 17. The system of claim 13, wherein the processor is further configured for: identifying movement of the identified visual cue, the identified movement including a set of coordinates of the visual cue at each of a plurality of points in time; and determining a target range associated with each of the sets of coordinates of the visual cue.
 18. The system of claim 13, wherein the processor is further configured for: recommending one or more training drills to the individual based on a score generated from scoring the movement of the individual's eye or eyes.
 19. The system of claim 13, wherein scoring the tracking of the individual's eye or eyes includes one or more of: generating a target score, generating a cognitive load score, and calculating a stress indicator score. 20-23. (canceled)
 24. A computer readable medium storing instructions that, when executed by a computer, cause the computer to perform a method of evaluating human eye tracking, the method including: receiving data representing the location of and/or information tracked by an individual's eye or eyes before, during, or after the individual performs a task; identifying a temporal phase or a biomechanical phase of the task performed by the individual; identifying a visual cue in the identified temporal phase or biomechanical phase; and scoring the tracking of the individual's eye or eyes by comparing the data to the visual cue. 